Decision-Making and Behavioral Economics

The breadth-depth dilemma in a finite capacity model of decision-making

The paper models decision-making under limited capacity, showing that optimal strategies shift from breadth to depth as capacity increases.

Temporal discounting correlates with directed exploration but not with random exploration

This study finds that temporal discounting correlates with directed exploration but not with random exploration in decision-making tasks.

Simulating future rewards: exploring the impacts of implicit context association and arithmetic booster in delay discounting

The paper investigates whether cognitive tasks linked to future thinking can reduce impulsivity in delay discounting but finds no clear evidence of effectiveness and highlights task repetition effects.

Human complex exploration strategies are extended via noradrenaline-modulated heuristics

The paper shows humans use computationally cheap exploration strategies, with value-free random exploration controlled by noradrenaline.

Hierarchical Network Model Excitatory-Inhibitory Tone Shapes Alternative Strategies for Different Degrees of Uncertainty in Multi-Attribute Decisions

The paper models decision-making in a hierarchical neural network, showing how excitatory-inhibitory balance affects decision strategies under different uncertainty levels.

GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

GLAMbox provides a Python toolbox for analyzing the relationship between gaze allocation and decision behavior using Bayesian models.

Autistic traits influence the strategic diversity of information sampling: insights from two-stage decision models

The paper examines how autistic traits affect information sampling strategies in a probabilistic inference task, finding trait-related differences in cost and evidence prioritization during decision-making.

Sensitivity to gains during risky decision-making differentiates chronic cocaine users from stimulant-naive controls

This study finds that chronic cocaine users show altered sensitivity to gain information during risky decision-making, leading to increased risk-seeking in unfavorable scenarios.

Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice

The paper investigates how low-level neural processes and high-level cognitive processes interact to influence context-dependent choice in humans, finding that both contribute to distinct behavioral patterns.

CHaRTr: An R toolbox for modeling Choices and Response Times in decision-making tasks

CHaRTr is an R toolbox that allows users to implement and test various decision-making models, including modern extensions of the diffusion decision model.

COMT Val158Met polymorphism associated with greater susceptibility to framing effects in healthy older adults

This study examines the association between COMT Val158Met polymorphism and susceptibility to framing effects in older adults, finding a significant link that diminishes after adjusting for demographic factors.

Choosing and learning: outcome valence differentially affects learning from free versus forced choices

The paper tests whether learning bias stems from positivity or choice-confirmation, finding stronger positive prediction errors in free-choice conditions.

Exploration-related strategy mediates negative coupling between decision-making performance and psychiatric symptoms

The paper identifies a psychiatric symptom dimension linked to decision-making performance through exploration strategies in a healthy population.

Optimal policy for multi-alternative decisions

The paper derives the optimal policy for multi-alternative decisions and shows how it can be implemented by a neural circuit with normalization and urgency signals.

Base-rate neglect and neural computations for subjective weight in probabilistic inference

The paper investigates base-rate neglect in probabilistic inference, showing it arises from neural computations in the orbitofrontal and medial prefrontal cortices that weight information sources.

An Analysis of Decision Under Risk in Rats

This study applies Prospect Theory to rats, showing they exhibit probability distortion and diminishing sensitivity similar to humans, suggesting shared neural mechanisms.

Context-dependent probability estimation and its neurocomputational substrates

The paper investigates how context influences probability estimation and identifies brain regions involved in this process.

Salience-driven value construction for adaptive choice under risk

The paper investigates how humans evaluate complex risky options by showing subjects use integrated value functions for individual outcomes and differential weighting based on reward magnitude or probability for overall value construction.

Gaze Bias Differences Capture Individual Choice Behavior

The paper investigates individual differences in the link between gaze behavior and choice behavior using a computational model applied to individual participants.

Do adolescents take more risks? Not when facing a novel uncertain situation

This study finds adolescents do not take more risks than children or adults in a novel uncertain situation, challenging the idea of increased risk-taking during adolescence.

A response to Zhang et al. (2018), \"Can Mouse-tracking Reveal Attribute Processing Speeds in Dietary Self-control? Commentary on Sullivan et al. (2015) and Lim et al. (2018)\"

The paper responds to Zhang et al. (2018) by reanalyzing mouse-tracking data to assess differences in attribute processing speeds during dietary self-control decisions.

Sources of suboptimality in a minimalistic explore-exploit task

The paper examines human behavior in a simplified explore-exploit task and finds deviations from optimal strategies, revealing a suboptimal switching rule and sequence-level variability.

Believing in one's power: a counterfactual heuristic for goal-directed control

The paper introduces a model of causal inference that explains how people perceive their causal power through counterfactual reasoning, showing it better explains behavior than alternative models.

Efficient coding of subjective value

The paper proposes an information-theoretic model of subjective value coding that explains variability in value reports and preference choices, and predicts a new preference illusion validated with empirical data.

Hard decisions shape the neural coding of preferences

This study shows that preferences change during decision-making, with neural activity and eye-tracking predicting these changes and their behavioral relevance at re-evaluation.

Optimizing sequential decisions in the drift-diffusion model

The paper develops a drift-diffusion model for sequential decision-making, showing how prior information affects future decisions and optimizing reward rates in correlated trial sequences.

Ongoing, rational calibration of reward-driven perceptual biases

This study shows that decision-making biases in monkeys can be explained by rational satisficing strategies rather than suboptimal learning or physical limitations.

Latent Structure of Risk Perception

The paper uses PCA to identify three latent components of risk-taking behavior from self-reports and behavioral tasks in young adults.

Counterfactual reasoning underlies the learning of priors in decision making

Participants learned base rates from decision-making without feedback by updating their beliefs using counterfactual confidence representations, improving accuracy and confidence.

Model-based fMRI reveals dissimilarity processes underlying base-rate neglect

The paper develops a hybrid computational model of the inverse base rate effect and uses fMRI to show that dissimilarity-based processing contributes to the effect, with activation patterns in left rostrolateral prefrontal cortex tracking model predictions.